Xiaofang Zhou

Efficient secure similarity computation on encrypted trajectory data

2015

Outsourcing database to clouds is a scalable and cost-effective way for large scale data storage, management, and query processing. Trajectory data contain rich spatio-temporal relationships and reveal many forms of individual sensitive information (e.g., home …

A Noise-aware Method with Type Constraint Pattern for Neural Relation Extraction

2021 · IEEE Transactions on Knowledge and Data Engineering

Distant supervision is an efficient way to generate large-scale training data for relation extraction without human efforts. However, the accompanying challenges have been plaguing the advance of the extractor: (1) the automatically annotated labels for …

Adapting to User Interest Drift for POI Recommendation

2016 · IEEE Transactions on Knowledge and Data Engineering

Point-of-Interest recommendation is an essential means to help people discover attractive locations, especially when people travel out of town or to unfamiliar regions. While a growing line of research has focused on modeling user geographical …

Joint Modeling of User Check-in Behaviors for Real-time Point-of-Interest Recommendation

2016 · ACM Transactions on Information Systems

Point-of-Interest (POI) recommendation has become an important means to help people discover attractive and interesting places, especially when users travel out of town. However, the extreme sparsity of a user-POI matrix creates a severe challenge. …

Spatial-Aware Hierarchical Collaborative Deep Learning for POI Recommendation

2017 · IEEE Transactions on Knowledge and Data Engineering

Point-of-interest (POI) recommendation has become an important way to help people discover attractive and interesting places, especially when they travel out of town. However, the extreme sparsity of user-POI matrix and cold-start issues severely hinder …

Joint Event-Partner Recommendation in Event-Based Social Networks

2018

With the prevalent trend of combining online and offline interactions among users in event-based social networks (EBSNs), event recommendation has become an essential means to help people discover new interesting events to attend. However, existing …

Where to Go Next: A Spatio-Temporal Gated Network for Next POI Recommendation

2019 · Proceedings of the AAAI Conference on Artificial Intelligence

Next Point-of-Interest (POI) recommendation is of great value for both location-based service providers and users. However, the state-of-the-art Recurrent Neural Networks (RNNs) rarely consider the spatio-temporal intervals between neighbor check-ins, which are essential for modeling …

Recurrent Convolutional Neural Network for Sequential Recommendation

2019

The sequential recommendation, which models sequential behavioral patterns among users for the recommendation, plays a critical role in recommender systems. However, the state-of-the-art Recurrent Neural Networks (RNN) solutions rarely consider the non-linear feature interactions and …

Social Influence-Based Group Representation Learning for Group Recommendation

2019

As social animals, attending group activities is an indispensable part in people's daily social life, and it is an important task for recommender systems to suggest satisfying activities to a group of users. The major …

Graph Contextualized Self-Attention Network for Session-based Recommendation

2019

Session-based recommendation, which aims to predict the user's immediate next action based on anonymous sessions, is a key task in many online services (e.g., e-commerce, media streaming). Recently, Self-Attention Network (SAN) has achieved significant success …

Feature-level Deeper Self-Attention Network for Sequential Recommendation

2019

Sequential recommendation, which aims to recommend next item that the user will likely interact in a near future, has become essential in various Internet applications. Existing methods usually consider the transition patterns between items, but …